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<div class="title">BesselFunctionsFunctors.h</div>  </div>
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<div class="contents">
<div class="fragment"><div class="line"><a name="l00001"></a><span class="lineno">    1</span>&#160;<span class="comment">// This file is part of Eigen, a lightweight C++ template library</span></div>
<div class="line"><a name="l00002"></a><span class="lineno">    2</span>&#160;<span class="comment">// for linear algebra.</span></div>
<div class="line"><a name="l00003"></a><span class="lineno">    3</span>&#160;<span class="comment">//</span></div>
<div class="line"><a name="l00004"></a><span class="lineno">    4</span>&#160;<span class="comment">// Copyright (C) 2016 Eugene Brevdo &lt;ebrevdo@gmail.com&gt;</span></div>
<div class="line"><a name="l00005"></a><span class="lineno">    5</span>&#160;<span class="comment">// Copyright (C) 2016 Gael Guennebaud &lt;gael.guennebaud@inria.fr&gt;</span></div>
<div class="line"><a name="l00006"></a><span class="lineno">    6</span>&#160;<span class="comment">//</span></div>
<div class="line"><a name="l00007"></a><span class="lineno">    7</span>&#160;<span class="comment">// This Source Code Form is subject to the terms of the Mozilla</span></div>
<div class="line"><a name="l00008"></a><span class="lineno">    8</span>&#160;<span class="comment">// Public License v. 2.0. If a copy of the MPL was not distributed</span></div>
<div class="line"><a name="l00009"></a><span class="lineno">    9</span>&#160;<span class="comment">// with this file, You can obtain one at http://mozilla.org/MPL/2.0/.</span></div>
<div class="line"><a name="l00010"></a><span class="lineno">   10</span>&#160; </div>
<div class="line"><a name="l00011"></a><span class="lineno">   11</span>&#160;<span class="preprocessor">#ifndef EIGEN_BESSELFUNCTIONS_FUNCTORS_H</span></div>
<div class="line"><a name="l00012"></a><span class="lineno">   12</span>&#160;<span class="preprocessor">#define EIGEN_BESSELFUNCTIONS_FUNCTORS_H</span></div>
<div class="line"><a name="l00013"></a><span class="lineno">   13</span>&#160; </div>
<div class="line"><a name="l00014"></a><span class="lineno">   14</span>&#160;<span class="preprocessor">#include &quot;./InternalHeaderCheck.h&quot;</span></div>
<div class="line"><a name="l00015"></a><span class="lineno">   15</span>&#160; </div>
<div class="line"><a name="l00016"></a><span class="lineno">   16</span>&#160;<span class="keyword">namespace </span><a class="code" href="namespaceEigen.html">Eigen</a> {</div>
<div class="line"><a name="l00017"></a><span class="lineno">   17</span>&#160; </div>
<div class="line"><a name="l00018"></a><span class="lineno">   18</span>&#160;<span class="keyword">namespace </span>internal {</div>
<div class="line"><a name="l00019"></a><span class="lineno">   19</span>&#160; </div>
<div class="line"><a name="l00025"></a><span class="lineno">   25</span>&#160;<span class="keyword">template</span> &lt;<span class="keyword">typename</span> Scalar&gt;</div>
<div class="line"><a name="l00026"></a><span class="lineno">   26</span>&#160;<span class="keyword">struct </span>scalar_bessel_i0_op {</div>
<div class="line"><a name="l00027"></a><span class="lineno">   27</span>&#160;  EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE <span class="keyword">const</span> Scalar operator()(<span class="keyword">const</span> Scalar&amp; x)<span class="keyword"> const </span>{</div>
<div class="line"><a name="l00028"></a><span class="lineno">   28</span>&#160;    <span class="keyword">using</span> numext::bessel_i0;</div>
<div class="line"><a name="l00029"></a><span class="lineno">   29</span>&#160;    <span class="keywordflow">return</span> <a class="code" href="namespaceEigen.html#ab0c429bb38ce58964b561fb9d6c9377a">bessel_i0</a>(x);</div>
<div class="line"><a name="l00030"></a><span class="lineno">   30</span>&#160;  }</div>
<div class="line"><a name="l00031"></a><span class="lineno">   31</span>&#160;  <span class="keyword">typedef</span> <span class="keyword">typename</span> packet_traits&lt;Scalar&gt;::type Packet;</div>
<div class="line"><a name="l00032"></a><span class="lineno">   32</span>&#160;  EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE Packet packetOp(<span class="keyword">const</span> Packet&amp; x)<span class="keyword"> const </span>{</div>
<div class="line"><a name="l00033"></a><span class="lineno">   33</span>&#160;    <span class="keywordflow">return</span> internal::pbessel_i0(x);</div>
<div class="line"><a name="l00034"></a><span class="lineno">   34</span>&#160;  }</div>
<div class="line"><a name="l00035"></a><span class="lineno">   35</span>&#160;};</div>
<div class="line"><a name="l00036"></a><span class="lineno">   36</span>&#160;<span class="keyword">template</span> &lt;<span class="keyword">typename</span> Scalar&gt;</div>
<div class="line"><a name="l00037"></a><span class="lineno">   37</span>&#160;<span class="keyword">struct </span>functor_traits&lt;scalar_bessel_i0_op&lt;Scalar&gt; &gt; {</div>
<div class="line"><a name="l00038"></a><span class="lineno">   38</span>&#160;  <span class="keyword">enum</span> {</div>
<div class="line"><a name="l00039"></a><span class="lineno">   39</span>&#160;    <span class="comment">// On average, a Chebyshev polynomial of order N=20 is computed.</span></div>
<div class="line"><a name="l00040"></a><span class="lineno">   40</span>&#160;    <span class="comment">// The cost is N multiplications and 2N additions. We also add</span></div>
<div class="line"><a name="l00041"></a><span class="lineno">   41</span>&#160;    <span class="comment">// the cost of an additional exp over i0e.</span></div>
<div class="line"><a name="l00042"></a><span class="lineno">   42</span>&#160;    Cost = 28 * NumTraits&lt;Scalar&gt;::MulCost + 48 * NumTraits&lt;Scalar&gt;::AddCost,</div>
<div class="line"><a name="l00043"></a><span class="lineno">   43</span>&#160;    PacketAccess = packet_traits&lt;Scalar&gt;::HasBessel</div>
<div class="line"><a name="l00044"></a><span class="lineno">   44</span>&#160;  };</div>
<div class="line"><a name="l00045"></a><span class="lineno">   45</span>&#160;};</div>
<div class="line"><a name="l00046"></a><span class="lineno">   46</span>&#160; </div>
<div class="line"><a name="l00052"></a><span class="lineno">   52</span>&#160;<span class="keyword">template</span> &lt;<span class="keyword">typename</span> Scalar&gt;</div>
<div class="line"><a name="l00053"></a><span class="lineno">   53</span>&#160;<span class="keyword">struct </span>scalar_bessel_i0e_op {</div>
<div class="line"><a name="l00054"></a><span class="lineno">   54</span>&#160;  EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE <span class="keyword">const</span> Scalar operator()(<span class="keyword">const</span> Scalar&amp; x)<span class="keyword"> const </span>{</div>
<div class="line"><a name="l00055"></a><span class="lineno">   55</span>&#160;    <span class="keyword">using</span> numext::bessel_i0e;</div>
<div class="line"><a name="l00056"></a><span class="lineno">   56</span>&#160;    <span class="keywordflow">return</span> <a class="code" href="namespaceEigen.html#aef13ab56dea757bfb7bd3e220ac478d5">bessel_i0e</a>(x);</div>
<div class="line"><a name="l00057"></a><span class="lineno">   57</span>&#160;  }</div>
<div class="line"><a name="l00058"></a><span class="lineno">   58</span>&#160;  <span class="keyword">typedef</span> <span class="keyword">typename</span> packet_traits&lt;Scalar&gt;::type Packet;</div>
<div class="line"><a name="l00059"></a><span class="lineno">   59</span>&#160;  EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE Packet packetOp(<span class="keyword">const</span> Packet&amp; x)<span class="keyword"> const </span>{</div>
<div class="line"><a name="l00060"></a><span class="lineno">   60</span>&#160;    <span class="keywordflow">return</span> internal::pbessel_i0e(x);</div>
<div class="line"><a name="l00061"></a><span class="lineno">   61</span>&#160;  }</div>
<div class="line"><a name="l00062"></a><span class="lineno">   62</span>&#160;};</div>
<div class="line"><a name="l00063"></a><span class="lineno">   63</span>&#160;<span class="keyword">template</span> &lt;<span class="keyword">typename</span> Scalar&gt;</div>
<div class="line"><a name="l00064"></a><span class="lineno">   64</span>&#160;<span class="keyword">struct </span>functor_traits&lt;scalar_bessel_i0e_op&lt;Scalar&gt; &gt; {</div>
<div class="line"><a name="l00065"></a><span class="lineno">   65</span>&#160;  <span class="keyword">enum</span> {</div>
<div class="line"><a name="l00066"></a><span class="lineno">   66</span>&#160;    <span class="comment">// On average, a Chebyshev polynomial of order N=20 is computed.</span></div>
<div class="line"><a name="l00067"></a><span class="lineno">   67</span>&#160;    <span class="comment">// The cost is N multiplications and 2N additions.</span></div>
<div class="line"><a name="l00068"></a><span class="lineno">   68</span>&#160;    Cost = 20 * NumTraits&lt;Scalar&gt;::MulCost + 40 * NumTraits&lt;Scalar&gt;::AddCost,</div>
<div class="line"><a name="l00069"></a><span class="lineno">   69</span>&#160;    PacketAccess = packet_traits&lt;Scalar&gt;::HasBessel</div>
<div class="line"><a name="l00070"></a><span class="lineno">   70</span>&#160;  };</div>
<div class="line"><a name="l00071"></a><span class="lineno">   71</span>&#160;};</div>
<div class="line"><a name="l00072"></a><span class="lineno">   72</span>&#160; </div>
<div class="line"><a name="l00078"></a><span class="lineno">   78</span>&#160;<span class="keyword">template</span> &lt;<span class="keyword">typename</span> Scalar&gt;</div>
<div class="line"><a name="l00079"></a><span class="lineno">   79</span>&#160;<span class="keyword">struct </span>scalar_bessel_i1_op {</div>
<div class="line"><a name="l00080"></a><span class="lineno">   80</span>&#160;  EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE <span class="keyword">const</span> Scalar operator()(<span class="keyword">const</span> Scalar&amp; x)<span class="keyword"> const </span>{</div>
<div class="line"><a name="l00081"></a><span class="lineno">   81</span>&#160;    <span class="keyword">using</span> numext::bessel_i1;</div>
<div class="line"><a name="l00082"></a><span class="lineno">   82</span>&#160;    <span class="keywordflow">return</span> <a class="code" href="namespaceEigen.html#ae35e1cabdc81f3783219186a7e658a2b">bessel_i1</a>(x);</div>
<div class="line"><a name="l00083"></a><span class="lineno">   83</span>&#160;  }</div>
<div class="line"><a name="l00084"></a><span class="lineno">   84</span>&#160;  <span class="keyword">typedef</span> <span class="keyword">typename</span> packet_traits&lt;Scalar&gt;::type Packet;</div>
<div class="line"><a name="l00085"></a><span class="lineno">   85</span>&#160;  EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE Packet packetOp(<span class="keyword">const</span> Packet&amp; x)<span class="keyword"> const </span>{</div>
<div class="line"><a name="l00086"></a><span class="lineno">   86</span>&#160;    <span class="keywordflow">return</span> internal::pbessel_i1(x);</div>
<div class="line"><a name="l00087"></a><span class="lineno">   87</span>&#160;  }</div>
<div class="line"><a name="l00088"></a><span class="lineno">   88</span>&#160;};</div>
<div class="line"><a name="l00089"></a><span class="lineno">   89</span>&#160;<span class="keyword">template</span> &lt;<span class="keyword">typename</span> Scalar&gt;</div>
<div class="line"><a name="l00090"></a><span class="lineno">   90</span>&#160;<span class="keyword">struct </span>functor_traits&lt;scalar_bessel_i1_op&lt;Scalar&gt; &gt; {</div>
<div class="line"><a name="l00091"></a><span class="lineno">   91</span>&#160;  <span class="keyword">enum</span> {</div>
<div class="line"><a name="l00092"></a><span class="lineno">   92</span>&#160;    <span class="comment">// On average, a Chebyshev polynomial of order N=20 is computed.</span></div>
<div class="line"><a name="l00093"></a><span class="lineno">   93</span>&#160;    <span class="comment">// The cost is N multiplications and 2N additions. We also add</span></div>
<div class="line"><a name="l00094"></a><span class="lineno">   94</span>&#160;    <span class="comment">// the cost of an additional exp over i1e.</span></div>
<div class="line"><a name="l00095"></a><span class="lineno">   95</span>&#160;    Cost = 28 * NumTraits&lt;Scalar&gt;::MulCost + 48 * NumTraits&lt;Scalar&gt;::AddCost,</div>
<div class="line"><a name="l00096"></a><span class="lineno">   96</span>&#160;    PacketAccess = packet_traits&lt;Scalar&gt;::HasBessel</div>
<div class="line"><a name="l00097"></a><span class="lineno">   97</span>&#160;  };</div>
<div class="line"><a name="l00098"></a><span class="lineno">   98</span>&#160;};</div>
<div class="line"><a name="l00099"></a><span class="lineno">   99</span>&#160; </div>
<div class="line"><a name="l00105"></a><span class="lineno">  105</span>&#160;<span class="keyword">template</span> &lt;<span class="keyword">typename</span> Scalar&gt;</div>
<div class="line"><a name="l00106"></a><span class="lineno">  106</span>&#160;<span class="keyword">struct </span>scalar_bessel_i1e_op {</div>
<div class="line"><a name="l00107"></a><span class="lineno">  107</span>&#160;  EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE <span class="keyword">const</span> Scalar operator()(<span class="keyword">const</span> Scalar&amp; x)<span class="keyword"> const </span>{</div>
<div class="line"><a name="l00108"></a><span class="lineno">  108</span>&#160;    <span class="keyword">using</span> numext::bessel_i1e;</div>
<div class="line"><a name="l00109"></a><span class="lineno">  109</span>&#160;    <span class="keywordflow">return</span> <a class="code" href="namespaceEigen.html#ae52c524c4108c6265e9543468da42e28">bessel_i1e</a>(x);</div>
<div class="line"><a name="l00110"></a><span class="lineno">  110</span>&#160;  }</div>
<div class="line"><a name="l00111"></a><span class="lineno">  111</span>&#160;  <span class="keyword">typedef</span> <span class="keyword">typename</span> packet_traits&lt;Scalar&gt;::type Packet;</div>
<div class="line"><a name="l00112"></a><span class="lineno">  112</span>&#160;  EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE Packet packetOp(<span class="keyword">const</span> Packet&amp; x)<span class="keyword"> const </span>{</div>
<div class="line"><a name="l00113"></a><span class="lineno">  113</span>&#160;    <span class="keywordflow">return</span> internal::pbessel_i1e(x);</div>
<div class="line"><a name="l00114"></a><span class="lineno">  114</span>&#160;  }</div>
<div class="line"><a name="l00115"></a><span class="lineno">  115</span>&#160;};</div>
<div class="line"><a name="l00116"></a><span class="lineno">  116</span>&#160;<span class="keyword">template</span> &lt;<span class="keyword">typename</span> Scalar&gt;</div>
<div class="line"><a name="l00117"></a><span class="lineno">  117</span>&#160;<span class="keyword">struct </span>functor_traits&lt;scalar_bessel_i1e_op&lt;Scalar&gt; &gt; {</div>
<div class="line"><a name="l00118"></a><span class="lineno">  118</span>&#160;  <span class="keyword">enum</span> {</div>
<div class="line"><a name="l00119"></a><span class="lineno">  119</span>&#160;    <span class="comment">// On average, a Chebyshev polynomial of order N=20 is computed.</span></div>
<div class="line"><a name="l00120"></a><span class="lineno">  120</span>&#160;    <span class="comment">// The cost is N multiplications and 2N additions.</span></div>
<div class="line"><a name="l00121"></a><span class="lineno">  121</span>&#160;    Cost = 20 * NumTraits&lt;Scalar&gt;::MulCost + 40 * NumTraits&lt;Scalar&gt;::AddCost,</div>
<div class="line"><a name="l00122"></a><span class="lineno">  122</span>&#160;    PacketAccess = packet_traits&lt;Scalar&gt;::HasBessel</div>
<div class="line"><a name="l00123"></a><span class="lineno">  123</span>&#160;  };</div>
<div class="line"><a name="l00124"></a><span class="lineno">  124</span>&#160;};</div>
<div class="line"><a name="l00125"></a><span class="lineno">  125</span>&#160; </div>
<div class="line"><a name="l00131"></a><span class="lineno">  131</span>&#160;<span class="keyword">template</span> &lt;<span class="keyword">typename</span> Scalar&gt;</div>
<div class="line"><a name="l00132"></a><span class="lineno">  132</span>&#160;<span class="keyword">struct </span>scalar_bessel_j0_op {</div>
<div class="line"><a name="l00133"></a><span class="lineno">  133</span>&#160;  EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE <span class="keyword">const</span> Scalar operator()(<span class="keyword">const</span> Scalar&amp; x)<span class="keyword"> const </span>{</div>
<div class="line"><a name="l00134"></a><span class="lineno">  134</span>&#160;    <span class="keyword">using</span> numext::bessel_j0;</div>
<div class="line"><a name="l00135"></a><span class="lineno">  135</span>&#160;    <span class="keywordflow">return</span> <a class="code" href="namespaceEigen.html#a65acfc33a2b6140a09af67e45928e037">bessel_j0</a>(x);</div>
<div class="line"><a name="l00136"></a><span class="lineno">  136</span>&#160;  }</div>
<div class="line"><a name="l00137"></a><span class="lineno">  137</span>&#160;  <span class="keyword">typedef</span> <span class="keyword">typename</span> packet_traits&lt;Scalar&gt;::type Packet;</div>
<div class="line"><a name="l00138"></a><span class="lineno">  138</span>&#160;  EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE Packet packetOp(<span class="keyword">const</span> Packet&amp; x)<span class="keyword"> const </span>{</div>
<div class="line"><a name="l00139"></a><span class="lineno">  139</span>&#160;    <span class="keywordflow">return</span> internal::pbessel_j0(x);</div>
<div class="line"><a name="l00140"></a><span class="lineno">  140</span>&#160;  }</div>
<div class="line"><a name="l00141"></a><span class="lineno">  141</span>&#160;};</div>
<div class="line"><a name="l00142"></a><span class="lineno">  142</span>&#160;<span class="keyword">template</span> &lt;<span class="keyword">typename</span> Scalar&gt;</div>
<div class="line"><a name="l00143"></a><span class="lineno">  143</span>&#160;<span class="keyword">struct </span>functor_traits&lt;scalar_bessel_j0_op&lt;Scalar&gt; &gt; {</div>
<div class="line"><a name="l00144"></a><span class="lineno">  144</span>&#160;  <span class="keyword">enum</span> {</div>
<div class="line"><a name="l00145"></a><span class="lineno">  145</span>&#160;    <span class="comment">// 6 polynomial of order ~N=8 is computed.</span></div>
<div class="line"><a name="l00146"></a><span class="lineno">  146</span>&#160;    <span class="comment">// The cost is N multiplications and N additions each, along with a</span></div>
<div class="line"><a name="l00147"></a><span class="lineno">  147</span>&#160;    <span class="comment">// sine, cosine and rsqrt cost.</span></div>
<div class="line"><a name="l00148"></a><span class="lineno">  148</span>&#160;    Cost = 63 * NumTraits&lt;Scalar&gt;::MulCost + 48 * NumTraits&lt;Scalar&gt;::AddCost,</div>
<div class="line"><a name="l00149"></a><span class="lineno">  149</span>&#160;    PacketAccess = packet_traits&lt;Scalar&gt;::HasBessel</div>
<div class="line"><a name="l00150"></a><span class="lineno">  150</span>&#160;  };</div>
<div class="line"><a name="l00151"></a><span class="lineno">  151</span>&#160;};</div>
<div class="line"><a name="l00152"></a><span class="lineno">  152</span>&#160; </div>
<div class="line"><a name="l00158"></a><span class="lineno">  158</span>&#160;<span class="keyword">template</span> &lt;<span class="keyword">typename</span> Scalar&gt;</div>
<div class="line"><a name="l00159"></a><span class="lineno">  159</span>&#160;<span class="keyword">struct </span>scalar_bessel_y0_op {</div>
<div class="line"><a name="l00160"></a><span class="lineno">  160</span>&#160;  EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE <span class="keyword">const</span> Scalar operator()(<span class="keyword">const</span> Scalar&amp; x)<span class="keyword"> const </span>{</div>
<div class="line"><a name="l00161"></a><span class="lineno">  161</span>&#160;    <span class="keyword">using</span> numext::bessel_y0;</div>
<div class="line"><a name="l00162"></a><span class="lineno">  162</span>&#160;    <span class="keywordflow">return</span> <a class="code" href="namespaceEigen.html#aad0c42bfd8d5b4169a542206b460b2d0">bessel_y0</a>(x);</div>
<div class="line"><a name="l00163"></a><span class="lineno">  163</span>&#160;  }</div>
<div class="line"><a name="l00164"></a><span class="lineno">  164</span>&#160;  <span class="keyword">typedef</span> <span class="keyword">typename</span> packet_traits&lt;Scalar&gt;::type Packet;</div>
<div class="line"><a name="l00165"></a><span class="lineno">  165</span>&#160;  EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE Packet packetOp(<span class="keyword">const</span> Packet&amp; x)<span class="keyword"> const </span>{</div>
<div class="line"><a name="l00166"></a><span class="lineno">  166</span>&#160;    <span class="keywordflow">return</span> internal::pbessel_y0(x);</div>
<div class="line"><a name="l00167"></a><span class="lineno">  167</span>&#160;  }</div>
<div class="line"><a name="l00168"></a><span class="lineno">  168</span>&#160;};</div>
<div class="line"><a name="l00169"></a><span class="lineno">  169</span>&#160;<span class="keyword">template</span> &lt;<span class="keyword">typename</span> Scalar&gt;</div>
<div class="line"><a name="l00170"></a><span class="lineno">  170</span>&#160;<span class="keyword">struct </span>functor_traits&lt;scalar_bessel_y0_op&lt;Scalar&gt; &gt; {</div>
<div class="line"><a name="l00171"></a><span class="lineno">  171</span>&#160;  <span class="keyword">enum</span> {</div>
<div class="line"><a name="l00172"></a><span class="lineno">  172</span>&#160;    <span class="comment">// 6 polynomial of order ~N=8 is computed.</span></div>
<div class="line"><a name="l00173"></a><span class="lineno">  173</span>&#160;    <span class="comment">// The cost is N multiplications and N additions each, along with a</span></div>
<div class="line"><a name="l00174"></a><span class="lineno">  174</span>&#160;    <span class="comment">// sine, cosine, rsqrt and j0 cost.</span></div>
<div class="line"><a name="l00175"></a><span class="lineno">  175</span>&#160;    Cost = 126 * NumTraits&lt;Scalar&gt;::MulCost + 96 * NumTraits&lt;Scalar&gt;::AddCost,</div>
<div class="line"><a name="l00176"></a><span class="lineno">  176</span>&#160;    PacketAccess = packet_traits&lt;Scalar&gt;::HasBessel</div>
<div class="line"><a name="l00177"></a><span class="lineno">  177</span>&#160;  };</div>
<div class="line"><a name="l00178"></a><span class="lineno">  178</span>&#160;};</div>
<div class="line"><a name="l00179"></a><span class="lineno">  179</span>&#160; </div>
<div class="line"><a name="l00185"></a><span class="lineno">  185</span>&#160;<span class="keyword">template</span> &lt;<span class="keyword">typename</span> Scalar&gt;</div>
<div class="line"><a name="l00186"></a><span class="lineno">  186</span>&#160;<span class="keyword">struct </span>scalar_bessel_j1_op {</div>
<div class="line"><a name="l00187"></a><span class="lineno">  187</span>&#160;  EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE <span class="keyword">const</span> Scalar operator()(<span class="keyword">const</span> Scalar&amp; x)<span class="keyword"> const </span>{</div>
<div class="line"><a name="l00188"></a><span class="lineno">  188</span>&#160;    <span class="keyword">using</span> numext::bessel_j1;</div>
<div class="line"><a name="l00189"></a><span class="lineno">  189</span>&#160;    <span class="keywordflow">return</span> <a class="code" href="namespaceEigen.html#a4079ddbfe44e3a865cdb600353f371ab">bessel_j1</a>(x);</div>
<div class="line"><a name="l00190"></a><span class="lineno">  190</span>&#160;  }</div>
<div class="line"><a name="l00191"></a><span class="lineno">  191</span>&#160;  <span class="keyword">typedef</span> <span class="keyword">typename</span> packet_traits&lt;Scalar&gt;::type Packet;</div>
<div class="line"><a name="l00192"></a><span class="lineno">  192</span>&#160;  EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE Packet packetOp(<span class="keyword">const</span> Packet&amp; x)<span class="keyword"> const </span>{</div>
<div class="line"><a name="l00193"></a><span class="lineno">  193</span>&#160;    <span class="keywordflow">return</span> internal::pbessel_j1(x);</div>
<div class="line"><a name="l00194"></a><span class="lineno">  194</span>&#160;  }</div>
<div class="line"><a name="l00195"></a><span class="lineno">  195</span>&#160;};</div>
<div class="line"><a name="l00196"></a><span class="lineno">  196</span>&#160;<span class="keyword">template</span> &lt;<span class="keyword">typename</span> Scalar&gt;</div>
<div class="line"><a name="l00197"></a><span class="lineno">  197</span>&#160;<span class="keyword">struct </span>functor_traits&lt;scalar_bessel_j1_op&lt;Scalar&gt; &gt; {</div>
<div class="line"><a name="l00198"></a><span class="lineno">  198</span>&#160;  <span class="keyword">enum</span> {</div>
<div class="line"><a name="l00199"></a><span class="lineno">  199</span>&#160;    <span class="comment">// 6 polynomial of order ~N=8 is computed.</span></div>
<div class="line"><a name="l00200"></a><span class="lineno">  200</span>&#160;    <span class="comment">// The cost is N multiplications and N additions each, along with a</span></div>
<div class="line"><a name="l00201"></a><span class="lineno">  201</span>&#160;    <span class="comment">// sine, cosine and rsqrt cost.</span></div>
<div class="line"><a name="l00202"></a><span class="lineno">  202</span>&#160;    Cost = 63 * NumTraits&lt;Scalar&gt;::MulCost + 48 * NumTraits&lt;Scalar&gt;::AddCost,</div>
<div class="line"><a name="l00203"></a><span class="lineno">  203</span>&#160;    PacketAccess = packet_traits&lt;Scalar&gt;::HasBessel</div>
<div class="line"><a name="l00204"></a><span class="lineno">  204</span>&#160;  };</div>
<div class="line"><a name="l00205"></a><span class="lineno">  205</span>&#160;};</div>
<div class="line"><a name="l00206"></a><span class="lineno">  206</span>&#160; </div>
<div class="line"><a name="l00212"></a><span class="lineno">  212</span>&#160;<span class="keyword">template</span> &lt;<span class="keyword">typename</span> Scalar&gt;</div>
<div class="line"><a name="l00213"></a><span class="lineno">  213</span>&#160;<span class="keyword">struct </span>scalar_bessel_y1_op {</div>
<div class="line"><a name="l00214"></a><span class="lineno">  214</span>&#160;  EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE <span class="keyword">const</span> Scalar operator()(<span class="keyword">const</span> Scalar&amp; x)<span class="keyword"> const </span>{</div>
<div class="line"><a name="l00215"></a><span class="lineno">  215</span>&#160;    <span class="keyword">using</span> numext::bessel_y1;</div>
<div class="line"><a name="l00216"></a><span class="lineno">  216</span>&#160;    <span class="keywordflow">return</span> <a class="code" href="namespaceEigen.html#a60d76185793d52703fa01d83d5b46615">bessel_y1</a>(x);</div>
<div class="line"><a name="l00217"></a><span class="lineno">  217</span>&#160;  }</div>
<div class="line"><a name="l00218"></a><span class="lineno">  218</span>&#160;  <span class="keyword">typedef</span> <span class="keyword">typename</span> packet_traits&lt;Scalar&gt;::type Packet;</div>
<div class="line"><a name="l00219"></a><span class="lineno">  219</span>&#160;  EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE Packet packetOp(<span class="keyword">const</span> Packet&amp; x)<span class="keyword"> const </span>{</div>
<div class="line"><a name="l00220"></a><span class="lineno">  220</span>&#160;    <span class="keywordflow">return</span> internal::pbessel_y1(x);</div>
<div class="line"><a name="l00221"></a><span class="lineno">  221</span>&#160;  }</div>
<div class="line"><a name="l00222"></a><span class="lineno">  222</span>&#160;};</div>
<div class="line"><a name="l00223"></a><span class="lineno">  223</span>&#160;<span class="keyword">template</span> &lt;<span class="keyword">typename</span> Scalar&gt;</div>
<div class="line"><a name="l00224"></a><span class="lineno">  224</span>&#160;<span class="keyword">struct </span>functor_traits&lt;scalar_bessel_y1_op&lt;Scalar&gt; &gt; {</div>
<div class="line"><a name="l00225"></a><span class="lineno">  225</span>&#160;  <span class="keyword">enum</span> {</div>
<div class="line"><a name="l00226"></a><span class="lineno">  226</span>&#160;    <span class="comment">// 6 polynomial of order ~N=8 is computed.</span></div>
<div class="line"><a name="l00227"></a><span class="lineno">  227</span>&#160;    <span class="comment">// The cost is N multiplications and N additions each, along with a</span></div>
<div class="line"><a name="l00228"></a><span class="lineno">  228</span>&#160;    <span class="comment">// sine, cosine, rsqrt and j1 cost.</span></div>
<div class="line"><a name="l00229"></a><span class="lineno">  229</span>&#160;    Cost = 126 * NumTraits&lt;Scalar&gt;::MulCost + 96 * NumTraits&lt;Scalar&gt;::AddCost,</div>
<div class="line"><a name="l00230"></a><span class="lineno">  230</span>&#160;    PacketAccess = packet_traits&lt;Scalar&gt;::HasBessel</div>
<div class="line"><a name="l00231"></a><span class="lineno">  231</span>&#160;  };</div>
<div class="line"><a name="l00232"></a><span class="lineno">  232</span>&#160;};</div>
<div class="line"><a name="l00233"></a><span class="lineno">  233</span>&#160; </div>
<div class="line"><a name="l00239"></a><span class="lineno">  239</span>&#160;<span class="keyword">template</span> &lt;<span class="keyword">typename</span> Scalar&gt;</div>
<div class="line"><a name="l00240"></a><span class="lineno">  240</span>&#160;<span class="keyword">struct </span>scalar_bessel_k0_op {</div>
<div class="line"><a name="l00241"></a><span class="lineno">  241</span>&#160;  EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE <span class="keyword">const</span> Scalar operator()(<span class="keyword">const</span> Scalar&amp; x)<span class="keyword"> const </span>{</div>
<div class="line"><a name="l00242"></a><span class="lineno">  242</span>&#160;    <span class="keyword">using</span> numext::bessel_k0;</div>
<div class="line"><a name="l00243"></a><span class="lineno">  243</span>&#160;    <span class="keywordflow">return</span> <a class="code" href="namespaceEigen.html#a4664123a5ae23d981410d7dc5cd86970">bessel_k0</a>(x);</div>
<div class="line"><a name="l00244"></a><span class="lineno">  244</span>&#160;  }</div>
<div class="line"><a name="l00245"></a><span class="lineno">  245</span>&#160;  <span class="keyword">typedef</span> <span class="keyword">typename</span> packet_traits&lt;Scalar&gt;::type Packet;</div>
<div class="line"><a name="l00246"></a><span class="lineno">  246</span>&#160;  EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE Packet packetOp(<span class="keyword">const</span> Packet&amp; x)<span class="keyword"> const </span>{</div>
<div class="line"><a name="l00247"></a><span class="lineno">  247</span>&#160;    <span class="keywordflow">return</span> internal::pbessel_k0(x);</div>
<div class="line"><a name="l00248"></a><span class="lineno">  248</span>&#160;  }</div>
<div class="line"><a name="l00249"></a><span class="lineno">  249</span>&#160;};</div>
<div class="line"><a name="l00250"></a><span class="lineno">  250</span>&#160;<span class="keyword">template</span> &lt;<span class="keyword">typename</span> Scalar&gt;</div>
<div class="line"><a name="l00251"></a><span class="lineno">  251</span>&#160;<span class="keyword">struct </span>functor_traits&lt;scalar_bessel_k0_op&lt;Scalar&gt; &gt; {</div>
<div class="line"><a name="l00252"></a><span class="lineno">  252</span>&#160;  <span class="keyword">enum</span> {</div>
<div class="line"><a name="l00253"></a><span class="lineno">  253</span>&#160;    <span class="comment">// On average, a Chebyshev polynomial of order N=10 is computed.</span></div>
<div class="line"><a name="l00254"></a><span class="lineno">  254</span>&#160;    <span class="comment">// The cost is N multiplications and 2N additions. In addition we compute</span></div>
<div class="line"><a name="l00255"></a><span class="lineno">  255</span>&#160;    <span class="comment">// i0, a log, exp and prsqrt and sin and cos.</span></div>
<div class="line"><a name="l00256"></a><span class="lineno">  256</span>&#160;    Cost = 68 * NumTraits&lt;Scalar&gt;::MulCost + 88 * NumTraits&lt;Scalar&gt;::AddCost,</div>
<div class="line"><a name="l00257"></a><span class="lineno">  257</span>&#160;    PacketAccess = packet_traits&lt;Scalar&gt;::HasBessel</div>
<div class="line"><a name="l00258"></a><span class="lineno">  258</span>&#160;  };</div>
<div class="line"><a name="l00259"></a><span class="lineno">  259</span>&#160;};</div>
<div class="line"><a name="l00260"></a><span class="lineno">  260</span>&#160; </div>
<div class="line"><a name="l00266"></a><span class="lineno">  266</span>&#160;<span class="keyword">template</span> &lt;<span class="keyword">typename</span> Scalar&gt;</div>
<div class="line"><a name="l00267"></a><span class="lineno">  267</span>&#160;<span class="keyword">struct </span>scalar_bessel_k0e_op {</div>
<div class="line"><a name="l00268"></a><span class="lineno">  268</span>&#160;  EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE <span class="keyword">const</span> Scalar operator()(<span class="keyword">const</span> Scalar&amp; x)<span class="keyword"> const </span>{</div>
<div class="line"><a name="l00269"></a><span class="lineno">  269</span>&#160;    <span class="keyword">using</span> numext::bessel_k0e;</div>
<div class="line"><a name="l00270"></a><span class="lineno">  270</span>&#160;    <span class="keywordflow">return</span> <a class="code" href="namespaceEigen.html#a9cc57448af6eda4fa72f34be7cc72da5">bessel_k0e</a>(x);</div>
<div class="line"><a name="l00271"></a><span class="lineno">  271</span>&#160;  }</div>
<div class="line"><a name="l00272"></a><span class="lineno">  272</span>&#160;  <span class="keyword">typedef</span> <span class="keyword">typename</span> packet_traits&lt;Scalar&gt;::type Packet;</div>
<div class="line"><a name="l00273"></a><span class="lineno">  273</span>&#160;  EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE Packet packetOp(<span class="keyword">const</span> Packet&amp; x)<span class="keyword"> const </span>{</div>
<div class="line"><a name="l00274"></a><span class="lineno">  274</span>&#160;    <span class="keywordflow">return</span> internal::pbessel_k0e(x);</div>
<div class="line"><a name="l00275"></a><span class="lineno">  275</span>&#160;  }</div>
<div class="line"><a name="l00276"></a><span class="lineno">  276</span>&#160;};</div>
<div class="line"><a name="l00277"></a><span class="lineno">  277</span>&#160;<span class="keyword">template</span> &lt;<span class="keyword">typename</span> Scalar&gt;</div>
<div class="line"><a name="l00278"></a><span class="lineno">  278</span>&#160;<span class="keyword">struct </span>functor_traits&lt;scalar_bessel_k0e_op&lt;Scalar&gt; &gt; {</div>
<div class="line"><a name="l00279"></a><span class="lineno">  279</span>&#160;  <span class="keyword">enum</span> {</div>
<div class="line"><a name="l00280"></a><span class="lineno">  280</span>&#160;    <span class="comment">// On average, a Chebyshev polynomial of order N=10 is computed.</span></div>
<div class="line"><a name="l00281"></a><span class="lineno">  281</span>&#160;    <span class="comment">// The cost is N multiplications and 2N additions. In addition we compute</span></div>
<div class="line"><a name="l00282"></a><span class="lineno">  282</span>&#160;    <span class="comment">// i0, a log, exp and prsqrt and sin and cos.</span></div>
<div class="line"><a name="l00283"></a><span class="lineno">  283</span>&#160;    Cost = 68 * NumTraits&lt;Scalar&gt;::MulCost + 88 * NumTraits&lt;Scalar&gt;::AddCost,</div>
<div class="line"><a name="l00284"></a><span class="lineno">  284</span>&#160;    PacketAccess = packet_traits&lt;Scalar&gt;::HasBessel</div>
<div class="line"><a name="l00285"></a><span class="lineno">  285</span>&#160;  };</div>
<div class="line"><a name="l00286"></a><span class="lineno">  286</span>&#160;};</div>
<div class="line"><a name="l00287"></a><span class="lineno">  287</span>&#160; </div>
<div class="line"><a name="l00293"></a><span class="lineno">  293</span>&#160;<span class="keyword">template</span> &lt;<span class="keyword">typename</span> Scalar&gt;</div>
<div class="line"><a name="l00294"></a><span class="lineno">  294</span>&#160;<span class="keyword">struct </span>scalar_bessel_k1_op {</div>
<div class="line"><a name="l00295"></a><span class="lineno">  295</span>&#160;  EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE <span class="keyword">const</span> Scalar operator()(<span class="keyword">const</span> Scalar&amp; x)<span class="keyword"> const </span>{</div>
<div class="line"><a name="l00296"></a><span class="lineno">  296</span>&#160;    <span class="keyword">using</span> numext::bessel_k1;</div>
<div class="line"><a name="l00297"></a><span class="lineno">  297</span>&#160;    <span class="keywordflow">return</span> <a class="code" href="namespaceEigen.html#a76e76fa84ed24785bf32665a48157bf1">bessel_k1</a>(x);</div>
<div class="line"><a name="l00298"></a><span class="lineno">  298</span>&#160;  }</div>
<div class="line"><a name="l00299"></a><span class="lineno">  299</span>&#160;  <span class="keyword">typedef</span> <span class="keyword">typename</span> packet_traits&lt;Scalar&gt;::type Packet;</div>
<div class="line"><a name="l00300"></a><span class="lineno">  300</span>&#160;  EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE Packet packetOp(<span class="keyword">const</span> Packet&amp; x)<span class="keyword"> const </span>{</div>
<div class="line"><a name="l00301"></a><span class="lineno">  301</span>&#160;    <span class="keywordflow">return</span> internal::pbessel_k1(x);</div>
<div class="line"><a name="l00302"></a><span class="lineno">  302</span>&#160;  }</div>
<div class="line"><a name="l00303"></a><span class="lineno">  303</span>&#160;};</div>
<div class="line"><a name="l00304"></a><span class="lineno">  304</span>&#160;<span class="keyword">template</span> &lt;<span class="keyword">typename</span> Scalar&gt;</div>
<div class="line"><a name="l00305"></a><span class="lineno">  305</span>&#160;<span class="keyword">struct </span>functor_traits&lt;scalar_bessel_k1_op&lt;Scalar&gt; &gt; {</div>
<div class="line"><a name="l00306"></a><span class="lineno">  306</span>&#160;  <span class="keyword">enum</span> {</div>
<div class="line"><a name="l00307"></a><span class="lineno">  307</span>&#160;    <span class="comment">// On average, a Chebyshev polynomial of order N=10 is computed.</span></div>
<div class="line"><a name="l00308"></a><span class="lineno">  308</span>&#160;    <span class="comment">// The cost is N multiplications and 2N additions. In addition we compute</span></div>
<div class="line"><a name="l00309"></a><span class="lineno">  309</span>&#160;    <span class="comment">// i1, a log, exp and prsqrt and sin and cos.</span></div>
<div class="line"><a name="l00310"></a><span class="lineno">  310</span>&#160;    Cost = 68 * NumTraits&lt;Scalar&gt;::MulCost + 88 * NumTraits&lt;Scalar&gt;::AddCost,</div>
<div class="line"><a name="l00311"></a><span class="lineno">  311</span>&#160;    PacketAccess = packet_traits&lt;Scalar&gt;::HasBessel</div>
<div class="line"><a name="l00312"></a><span class="lineno">  312</span>&#160;  };</div>
<div class="line"><a name="l00313"></a><span class="lineno">  313</span>&#160;};</div>
<div class="line"><a name="l00314"></a><span class="lineno">  314</span>&#160; </div>
<div class="line"><a name="l00320"></a><span class="lineno">  320</span>&#160;<span class="keyword">template</span> &lt;<span class="keyword">typename</span> Scalar&gt;</div>
<div class="line"><a name="l00321"></a><span class="lineno">  321</span>&#160;<span class="keyword">struct </span>scalar_bessel_k1e_op {</div>
<div class="line"><a name="l00322"></a><span class="lineno">  322</span>&#160;  EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE <span class="keyword">const</span> Scalar operator()(<span class="keyword">const</span> Scalar&amp; x)<span class="keyword"> const </span>{</div>
<div class="line"><a name="l00323"></a><span class="lineno">  323</span>&#160;    <span class="keyword">using</span> numext::bessel_k1e;</div>
<div class="line"><a name="l00324"></a><span class="lineno">  324</span>&#160;    <span class="keywordflow">return</span> <a class="code" href="namespaceEigen.html#af9e044c2baa913adea597c4d497a3315">bessel_k1e</a>(x);</div>
<div class="line"><a name="l00325"></a><span class="lineno">  325</span>&#160;  }</div>
<div class="line"><a name="l00326"></a><span class="lineno">  326</span>&#160;  <span class="keyword">typedef</span> <span class="keyword">typename</span> packet_traits&lt;Scalar&gt;::type Packet;</div>
<div class="line"><a name="l00327"></a><span class="lineno">  327</span>&#160;  EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE Packet packetOp(<span class="keyword">const</span> Packet&amp; x)<span class="keyword"> const </span>{</div>
<div class="line"><a name="l00328"></a><span class="lineno">  328</span>&#160;    <span class="keywordflow">return</span> internal::pbessel_k1e(x);</div>
<div class="line"><a name="l00329"></a><span class="lineno">  329</span>&#160;  }</div>
<div class="line"><a name="l00330"></a><span class="lineno">  330</span>&#160;};</div>
<div class="line"><a name="l00331"></a><span class="lineno">  331</span>&#160;<span class="keyword">template</span> &lt;<span class="keyword">typename</span> Scalar&gt;</div>
<div class="line"><a name="l00332"></a><span class="lineno">  332</span>&#160;<span class="keyword">struct </span>functor_traits&lt;scalar_bessel_k1e_op&lt;Scalar&gt; &gt; {</div>
<div class="line"><a name="l00333"></a><span class="lineno">  333</span>&#160;  <span class="keyword">enum</span> {</div>
<div class="line"><a name="l00334"></a><span class="lineno">  334</span>&#160;    <span class="comment">// On average, a Chebyshev polynomial of order N=10 is computed.</span></div>
<div class="line"><a name="l00335"></a><span class="lineno">  335</span>&#160;    <span class="comment">// The cost is N multiplications and 2N additions. In addition we compute</span></div>
<div class="line"><a name="l00336"></a><span class="lineno">  336</span>&#160;    <span class="comment">// i1, a log, exp and prsqrt and sin and cos.</span></div>
<div class="line"><a name="l00337"></a><span class="lineno">  337</span>&#160;    Cost = 68 * NumTraits&lt;Scalar&gt;::MulCost + 88 * NumTraits&lt;Scalar&gt;::AddCost,</div>
<div class="line"><a name="l00338"></a><span class="lineno">  338</span>&#160;    PacketAccess = packet_traits&lt;Scalar&gt;::HasBessel</div>
<div class="line"><a name="l00339"></a><span class="lineno">  339</span>&#160;  };</div>
<div class="line"><a name="l00340"></a><span class="lineno">  340</span>&#160;};</div>
<div class="line"><a name="l00341"></a><span class="lineno">  341</span>&#160; </div>
<div class="line"><a name="l00342"></a><span class="lineno">  342</span>&#160; </div>
<div class="line"><a name="l00343"></a><span class="lineno">  343</span>&#160;} <span class="comment">// end namespace internal</span></div>
<div class="line"><a name="l00344"></a><span class="lineno">  344</span>&#160; </div>
<div class="line"><a name="l00345"></a><span class="lineno">  345</span>&#160;} <span class="comment">// end namespace Eigen</span></div>
<div class="line"><a name="l00346"></a><span class="lineno">  346</span>&#160; </div>
<div class="line"><a name="l00347"></a><span class="lineno">  347</span>&#160;<span class="preprocessor">#endif </span><span class="comment">// EIGEN_BESSELFUNCTIONS_FUNCTORS_H</span></div>
<div class="ttc" id="anamespaceEigen_html"><div class="ttname"><a href="namespaceEigen.html">Eigen</a></div><div class="ttdoc">Namespace containing all symbols from the Eigen library.</div></div>
<div class="ttc" id="anamespaceEigen_html_a4079ddbfe44e3a865cdb600353f371ab"><div class="ttname"><a href="namespaceEigen.html#a4079ddbfe44e3a865cdb600353f371ab">Eigen::bessel_j1</a></div><div class="ttdeci">const Eigen::CwiseUnaryOp&lt; Eigen::internal::scalar_bessel_j1_op&lt; typename Derived::Scalar &gt;, const Derived &gt; bessel_j1(const Eigen::ArrayBase&lt; Derived &gt; &amp;x)</div><div class="ttdef"><b>Definition:</b> BesselFunctionsArrayAPI.h:258</div></div>
<div class="ttc" id="anamespaceEigen_html_a4664123a5ae23d981410d7dc5cd86970"><div class="ttname"><a href="namespaceEigen.html#a4664123a5ae23d981410d7dc5cd86970">Eigen::bessel_k0</a></div><div class="ttdeci">const Eigen::CwiseUnaryOp&lt; Eigen::internal::scalar_bessel_k0_op&lt; typename Derived::Scalar &gt;, const Derived &gt; bessel_k0(const Eigen::ArrayBase&lt; Derived &gt; &amp;x)</div><div class="ttdef"><b>Definition:</b> BesselFunctionsArrayAPI.h:124</div></div>
<div class="ttc" id="anamespaceEigen_html_a60d76185793d52703fa01d83d5b46615"><div class="ttname"><a href="namespaceEigen.html#a60d76185793d52703fa01d83d5b46615">Eigen::bessel_y1</a></div><div class="ttdeci">const Eigen::CwiseUnaryOp&lt; Eigen::internal::scalar_bessel_y1_op&lt; typename Derived::Scalar &gt;, const Derived &gt; bessel_y1(const Eigen::ArrayBase&lt; Derived &gt; &amp;x)</div><div class="ttdef"><b>Definition:</b> BesselFunctionsArrayAPI.h:280</div></div>
<div class="ttc" id="anamespaceEigen_html_a65acfc33a2b6140a09af67e45928e037"><div class="ttname"><a href="namespaceEigen.html#a65acfc33a2b6140a09af67e45928e037">Eigen::bessel_j0</a></div><div class="ttdeci">const Eigen::CwiseUnaryOp&lt; Eigen::internal::scalar_bessel_j0_op&lt; typename Derived::Scalar &gt;, const Derived &gt; bessel_j0(const Eigen::ArrayBase&lt; Derived &gt; &amp;x)</div><div class="ttdef"><b>Definition:</b> BesselFunctionsArrayAPI.h:214</div></div>
<div class="ttc" id="anamespaceEigen_html_a76e76fa84ed24785bf32665a48157bf1"><div class="ttname"><a href="namespaceEigen.html#a76e76fa84ed24785bf32665a48157bf1">Eigen::bessel_k1</a></div><div class="ttdeci">const Eigen::CwiseUnaryOp&lt; Eigen::internal::scalar_bessel_k1_op&lt; typename Derived::Scalar &gt;, const Derived &gt; bessel_k1(const Eigen::ArrayBase&lt; Derived &gt; &amp;x)</div><div class="ttdef"><b>Definition:</b> BesselFunctionsArrayAPI.h:169</div></div>
<div class="ttc" id="anamespaceEigen_html_a9cc57448af6eda4fa72f34be7cc72da5"><div class="ttname"><a href="namespaceEigen.html#a9cc57448af6eda4fa72f34be7cc72da5">Eigen::bessel_k0e</a></div><div class="ttdeci">const Eigen::CwiseUnaryOp&lt; Eigen::internal::scalar_bessel_k0e_op&lt; typename Derived::Scalar &gt;, const Derived &gt; bessel_k0e(const Eigen::ArrayBase&lt; Derived &gt; &amp;x)</div><div class="ttdef"><b>Definition:</b> BesselFunctionsArrayAPI.h:147</div></div>
<div class="ttc" id="anamespaceEigen_html_aad0c42bfd8d5b4169a542206b460b2d0"><div class="ttname"><a href="namespaceEigen.html#aad0c42bfd8d5b4169a542206b460b2d0">Eigen::bessel_y0</a></div><div class="ttdeci">const Eigen::CwiseUnaryOp&lt; Eigen::internal::scalar_bessel_y0_op&lt; typename Derived::Scalar &gt;, const Derived &gt; bessel_y0(const Eigen::ArrayBase&lt; Derived &gt; &amp;x)</div><div class="ttdef"><b>Definition:</b> BesselFunctionsArrayAPI.h:236</div></div>
<div class="ttc" id="anamespaceEigen_html_ab0c429bb38ce58964b561fb9d6c9377a"><div class="ttname"><a href="namespaceEigen.html#ab0c429bb38ce58964b561fb9d6c9377a">Eigen::bessel_i0</a></div><div class="ttdeci">const Eigen::CwiseUnaryOp&lt; Eigen::internal::scalar_bessel_i0_op&lt; typename Derived::Scalar &gt;, const Derived &gt; bessel_i0(const Eigen::ArrayBase&lt; Derived &gt; &amp;x)</div><div class="ttdef"><b>Definition:</b> BesselFunctionsArrayAPI.h:34</div></div>
<div class="ttc" id="anamespaceEigen_html_ae35e1cabdc81f3783219186a7e658a2b"><div class="ttname"><a href="namespaceEigen.html#ae35e1cabdc81f3783219186a7e658a2b">Eigen::bessel_i1</a></div><div class="ttdeci">const Eigen::CwiseUnaryOp&lt; Eigen::internal::scalar_bessel_i1_op&lt; typename Derived::Scalar &gt;, const Derived &gt; bessel_i1(const Eigen::ArrayBase&lt; Derived &gt; &amp;x)</div><div class="ttdef"><b>Definition:</b> BesselFunctionsArrayAPI.h:79</div></div>
<div class="ttc" id="anamespaceEigen_html_ae52c524c4108c6265e9543468da42e28"><div class="ttname"><a href="namespaceEigen.html#ae52c524c4108c6265e9543468da42e28">Eigen::bessel_i1e</a></div><div class="ttdeci">const Eigen::CwiseUnaryOp&lt; Eigen::internal::scalar_bessel_i1e_op&lt; typename Derived::Scalar &gt;, const Derived &gt; bessel_i1e(const Eigen::ArrayBase&lt; Derived &gt; &amp;x)</div><div class="ttdef"><b>Definition:</b> BesselFunctionsArrayAPI.h:102</div></div>
<div class="ttc" id="anamespaceEigen_html_aef13ab56dea757bfb7bd3e220ac478d5"><div class="ttname"><a href="namespaceEigen.html#aef13ab56dea757bfb7bd3e220ac478d5">Eigen::bessel_i0e</a></div><div class="ttdeci">const Eigen::CwiseUnaryOp&lt; Eigen::internal::scalar_bessel_i0e_op&lt; typename Derived::Scalar &gt;, const Derived &gt; bessel_i0e(const Eigen::ArrayBase&lt; Derived &gt; &amp;x)</div><div class="ttdef"><b>Definition:</b> BesselFunctionsArrayAPI.h:57</div></div>
<div class="ttc" id="anamespaceEigen_html_af9e044c2baa913adea597c4d497a3315"><div class="ttname"><a href="namespaceEigen.html#af9e044c2baa913adea597c4d497a3315">Eigen::bessel_k1e</a></div><div class="ttdeci">const Eigen::CwiseUnaryOp&lt; Eigen::internal::scalar_bessel_k1e_op&lt; typename Derived::Scalar &gt;, const Derived &gt; bessel_k1e(const Eigen::ArrayBase&lt; Derived &gt; &amp;x)</div><div class="ttdef"><b>Definition:</b> BesselFunctionsArrayAPI.h:192</div></div>
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